中山大学学报（自然科学版）Issue(4)：1-7,7.
基于 Gabor 小波和局部二值模式的步态识别
Gait Recognition Based on Gabor Wavelet and Local Binary Pattern
摘要
Abstract
Recently , gait recognition for individual identification has been attracting increasing attention from biometrics researchers .It is well known that Gait Energy Image ( GEI) is an efficient representation for gait, and Local Binary Pattern ( LBP) can extract the local information efficiently , but the information lack of the orientation and scale characteristic , Gabor wavelet can extract the feature of different orienta-tion and scales.First, using Gabor wavelet to extract the different orientation and scales'information of GEI, the magnitude spectral image is obtained .Second, LBP is used to extract the local information from magnitude spectral image , it can extract more local orientation and scale feature than the method of di-rectly use LBP on GEI .At last , as the dimension of the LBP feature is usually very high , this paper em-ploys a popular method called Discriminative Common Vectors ( DCV ) for further dimensionality reduc-tion, which minimizes the within-class distance and maximizes the between-class distance as much as possible.Finally, for simplicity consideration, the nearest neighbor classifier to classification is used . Experimental results on CASIA databases show that our algorithm is effective and obtains high recognition rates.Further, a sample expand method is proposed for the small sample problem in gait recognition , the method increase the recognition rates .关键词
步态能量图/Gabor小波/局部二值模式/辨识共同向量/维数约减/样本扩充/步态识别Key words
gait energy image/Gabor wavelet/local binary pattern/discriminant common vector/di-mension reduction/sample expand/gait recognition分类
计算机与自动化引用本文复制引用
刘志勇,杨关,冯国灿..基于 Gabor 小波和局部二值模式的步态识别[J].中山大学学报（自然科学版）,2014,(4):1-7,7.基金项目
国家自然科学基金资助项目（61272338，60975083，31100958）；河南省基础与前沿技术研究计划资助项目 （）
